Commentary

Many problems are associated with the economic evaluation and provision of public goods. How should communities proceed with the installation of LED streetlights in order to ensure that there is allocative efficiency, with the social surplus being maximized where marginal social cost=marginal social benefit (MSC=MSB)?

Streetlights are public goods because they are non-rivalrous and non-excludable. This causes complications when attempting to analyze their advantages (Figure 1).

Figure 1: Cost/benefit model for sodium and LED streetlights

The MSC1 curve represents the supply curve of sodium streetlights. The marginal private benefit (MPB), or demand curve for streetlights, does not intersect with the MSC curve because streetlights are public goods. This signifies that the free rider problem is occurring; no-one (or, in reality, very few people) will buy the good because they are all waiting for someone else to buy it. However, the city government ought to pay for these goods, as the MSB of streetlights is high. Before the implementation of LEDs, the optimum or efficient output was Q1 where the MSB curve intersects the MSC1 curve.

Although the article mentions that LEDs “cost the same”, the MSC2 curve for LED streetlights is below the MSC1 curve. This is because private costs are lower, and “energy savings can be as much as 50 percent”, signifying that the costs of using the lights, for many years after implementation, will decrease significantly.

Therefore, the MSC curve will drop. Simultaneously, the efficient quantity of LED streetlights the city ought to acquire will increase from Q1 to Q2. From the diagram, it can be seen that the city can reduce the costs spent on streetlights and at the same time obtain more. The extra lights can be stored until some need to be replaced, implying that costs in the budget for future purchases of the replacement of lights can also be saved.

However, the disadvantages of LED are associated health problems, namely an external cost of consumption (Figure 2).

Figure 2: Negative Consumption Externality of LED streetlights

Because streetlights are public goods, the D (MPB) curve has been shown to be almost irrelevant to the model. Instead, the externality (“health implications” of “increased diabetes and depression”) is shown by the downwards shift of the MSB1 curve to MSB2. The marginal external cost notated in the diagram supposedly measures the per unit negative impact of individual health problems on society.

The diagram shows that the efficient quantity of LEDs is not QP (initially predicted quantity), but QA (actual quantity). It also implies that in order to dissuade cities from implementing harmful LED lights, the efficient “price” of the LED lights at QA will not be cost/benefit2, where MSB2=MSC, but instead at cost/benefit3.

This diagram supports Fort Collins’ argument for changing only part of the city’s streetlights to LED lighting. It illustrates that because of the negative externality, LED lighting, while apparently more “cost-efficient”, has problems. However, the negative externality is probably not so large that LED lighting should be completely eliminated from the city government’s options. It makes sense for Fort Collins to “swap one third of its streetlights to LEDs”. Furthermore, Fort Collins mentioned that they hope to “install 3000 and 4000 Kelvin lights with varying brightness” and “study the results” before making further decisions about whether they will replace the rest of the city’s lights. This exemplifies how communities may use economic models to assess the advantages and disadvantages of public goods, with the aim of improving the well-being of their citizens and reaching allocative efficiency.

However, there are also many limitations to the models above. The models are all static, and do not reflect development of LEDs; an example of rapidly improving, new and clean technology. Research has probably been conducted in order to reduce harmful blue light, and costs of the lights have also been reduced. As the article suggests, the cities have probably taken measures to reduce negative impacts, such as warmer lights, shielding and dimming.

Additionally, more variables should be considered. For instance, the article mentions positive externalities of consumption of LEDs due to the ability to preserve darker night skies. There are also problems associated with LED light patterns being narrow and therefore posing danger of bear attacks. The city must consider different aspects because LEDs are public goods which need to benefit citizens, not only the city budget.

Finally, all the curves and points on the models are qualitative; although they reflect directional shifts, it is impossible to determine the monetary cost of negative and positive externalities. Therefore, applying corrections based on these static models will be unrealistic.

In conclusion, analysis shows that installation of LEDs in some streetlights will save costs while minimizing negative externalities. However, in order to ensure that allocative efficiency is improved, the city government should closely monitor effects on society and citizens’ feedback to make decisions based on reality rather than just on the abstract models.